SDaaS: Framework of Sensor Data as a Service for Leveraging Services in Internet of Things

Manujakshi, B. C.; Ramesh, K.

doi:10.1007/978-981-10-4741-1_32

Cited by 2 publications

(2 citation statements)

References 18 publications

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“…The proposed study is a continuation of our prior implementation of [34] and [35]. This framework will be more focused towards extraction of knowledge discovery from the complex sensory data.…”

Section: System Architecturementioning

confidence: 99%

Framework for cost-effective analytical modelling for sensory data over cloud environment

Bc¹,

Ramesh²

2019

IJECE

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In order to offer sensory data as a service over the cloud, it is necessary to execute a cost-effective and yet precise data analytical logic within the sensing units. However, it is quite questionable as such forms of analytical operation are quite resource dependent which cannot be offered by the resource constraint sensory units. Therefore, the proposed paper introduces a novel approach of performing cost-effective data analytical method in order to extract knowledge from big data over the cloud. The proposed study uses a novel concept of the frequent pattern along with a tree-based approach in order to develop an analytical model for carrying out the mining operation in the large-scale sensor deployment over the cloud environment. Using a simulation-based approach over the mathematical model, the proposed model exhibit reduced mining duration, controlled energy dissipation, and highly optimized memory demands for all the resource constraint nodes.

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Section: System Architecturementioning

confidence: 99%

Framework for cost-effective analytical modelling for sensory data over cloud environment

Bc¹,

Ramesh²

2019

IJECE

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“…This could be applicable by giving software agents running in the cloud, likewise alluded to as virtual sensors that act simply like physical sensors dispersed in the cloud, giving the environmental circumstances from the zone where they are deployed. Along these lines, this is the so-called sensor-data-as-a-service (SDaaS) paradigm [24]. This paradigm lessens the excess data capture as data reusability in WSNs that is straightforward to the cloud users.…”

Section: Introductionmentioning

confidence: 99%

Design and Implementation of a Sensor-Cloud Platform for Physical Sensor Management on CoT Environments

et al. 2018

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The development of the Internet of Things (IoT) has increased the ubiquity of the Internet by integrating all objects for interaction via embedded systems, leading to a highly distributed network of devices communicating with human beings as well as other devices. In recent years, cloud computing has attracted a lot of attention from specialists and experts around the world. With the increasing number of distributed sensor nodes in wireless sensor networks, new models for interacting with wireless sensors using the cloud are intended to overcome restricted resources and efficiency. In this paper, we propose a novel sensor-cloud based platform which is able to virtualize physical sensors as virtual sensors in the CoT (Cloud of Things) environment. Virtual sensors, which are the essentials of this sensor-cloud architecture, simplify the process of generating a multiuser environment over resource-constrained physical wireless sensors and can help in implementing applications across different domains. Virtual sensors are dynamically provided in a group which advantages capability of the management the designed platform. An auto-detection approach on the basis of virtual sensors is additionally proposed to identify the accessible physical sensors nodes even if the status of these sensors are offline. In order to assess the usability of the designed platform, a smart-space-based IoT case study was implemented, and a series of experiments were carried out to evaluate the proposed system performance. Furthermore, a comparison analysis was made and the results indicate that the proposed platform outperforms the existing platforms in numerous respects.

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SDaaS: Framework of Sensor Data as a Service for Leveraging Services in Internet of Things

Cited by 2 publications

References 18 publications

Framework for cost-effective analytical modelling for sensory data over cloud environment

Framework for cost-effective analytical modelling for sensory data over cloud environment

Design and Implementation of a Sensor-Cloud Platform for Physical Sensor Management on CoT Environments

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